AI Quality Enablement Lead

Cigna Health and Life Insurance Company; Glasgow; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Private Medical Insurance

Employee Wellbeing Benefits

Educational Development Program

Job summary

Cigna Healthcare is accelerating AI-enabled practices across Quality Engineering to improve quality, automation, and delivery outcomes. You will work with Scrum teams to implement AI-driven testing, tooling, and governance, designing accelerators and PoCs that scale across projects.

The role requires strong QE fundamentals, experience with AI-enabled software development, and collaboration across cross-functional teams in a hybrid setting.

Qualifications

• Strong foundation in Quality Engineering principles and practices.
• Experience with AI-enabled software development and AI-assisted QA.
• Knowledge of Agile, DevOps, CI/CD in modern delivery contexts.
• Experience defining standards and governance for AI usage across teams.

Responsibilities

• Drive adoption of AI-enabled Quality Engineering practices across teams.
• Define standards, guidance, and guardrails for responsible AI use in QE.
• Design, prototype, and evaluate AI-enabled testing, automation, and QA solutions.
• Integrate AI tools into QE processes to improve testing and delivery outcomes.
• Collaborate with Scrum teams to improve quality, automation, and CI/CD adoption.
• Monitor adoption and report KPIs with dashboards and scorecards.
• Lead workshops and knowledge-sharing to build AI capability across teams.

Skills

Quality Engineering

AI & Generative AI

Prompting techniques

Agile delivery

DevOps CI/CD

Tools

Microsoft Copilot

GitHub Copilot

Azure AI

OpenAI

AWS AI

Job description

Cigna Healthcare is accelerating AI-enabled practices across Quality Engineering to improve quality, automation, and delivery outcomes. You will work with Scrum teams to implement AI-driven testing, tooling, and governance, designing accelerators and PoCs that scale across projects.

The role requires strong QE fundamentals, experience with AI-enabled software development, and collaboration across cross-functional teams in a hybrid setting.